Ding, LiJoshi, AnupamPeng, YunPan, RongReddivari, Pavan2018-12-072018-12-072005-09-01http://hdl.handle.net/11603/12189The Semantic Web provides a way to encode information and knowledge on web pages in a form that is easier for computers to understand and process. This article discusses the issues underlying the discovery, indexing and search over web documents that contain semantic web markup. Unlike conventional Web search engines, which use information retrieval techniques designed for documents of unstructured text, Semantic Web search engines must handle documents comprised of semi-structured data. Moreover, the meaning of data is defined by associated ontologies that are also encoded as semantic web documents whose processing may require significant amount of reasoning. We describe Swoogle, an implemented semantic web search engine that discovers, analyzes, and indexes knowledge encoded in semantic web documents throughout the Web, and illustrate its use to help human users and software agents find relevant knowledge.28 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.information retrievalsemantic webswoogleUMBC Ebiquity Research GroupText